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A model of social influence on body mass index

dc.contributor.authorHammond, Ross A.en_US
dc.contributor.authorOrnstein, Joseph T.en_US
dc.date.accessioned2015-01-07T15:23:26Z
dc.date.availableWITHHELD_12_MONTHSen_US
dc.date.available2015-01-07T15:23:26Z
dc.date.issued2014-12en_US
dc.identifier.citationHammond, Ross A.; Ornstein, Joseph T. (2014). "A model of social influence on body mass index." Annals of the New York Academy of Sciences 1331(1): 34-42.en_US
dc.identifier.issn0077-8923en_US
dc.identifier.issn1749-6632en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/109867
dc.publisherOxford University Pressen_US
dc.publisherWiley Periodicals, Inc.en_US
dc.subject.otherObesityen_US
dc.subject.otherBody Weight Normsen_US
dc.subject.otherSocial Influenceen_US
dc.subject.otherAgent‐Based Modelingen_US
dc.titleA model of social influence on body mass indexen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelScience (General)en_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/109867/1/nyas12344.pdf
dc.identifier.doi10.1111/nyas.12344en_US
dc.identifier.sourceAnnals of the New York Academy of Sciencesen_US
dc.identifier.citedreferenceNakamaru, M. & S.A. Levin. 2004. Spread of two linked social norms on complex interaction networks. J. Theor. Biol. 230: 57 – 65.en_US
dc.identifier.citedreferenceGovernment of the Province of Québec, Canada. Quebec En Forme Project [computer file]. Trois‐Rivières, Canada: 2012.en_US
dc.identifier.citedreferenceThompson, M.A. & J.J. Gray. 1995. Development and validation of a new body‐image assessment scale. J. Pers. Assess. 64: 258 – 269.en_US
dc.identifier.citedreferenceUrberg, K.A. et al. 1995. The structure of adolescent peer networks. Dev. Psychol. 31: 540 – 547.en_US
dc.identifier.citedreferenceMercken, L. et al. 2010. Smoking‐based selection and influence in gender‐segregated friendship networks: a social network analysis of adolescent smoking. Addiction 105: 1280 – 1289.en_US
dc.identifier.citedreferenceDuncan, D.T. et al. 2011. Does perception equal reality? Weight misperception in relation to weight‐related attitudes and behaviors among overweight US and obese US adults. Int. J. Behav. Nutr. Phys. Activ. 8: 20.en_US
dc.identifier.citedreferenceRosin, O. 2012. Weight‐loss dieting behavior: an economic analysis. Health Econ. 21: 825 – 838.en_US
dc.identifier.citedreferenceCentola, D., R. Willer, & M. Macy. 2005. The emperor's dilemma: a computational model of self‐enforcing norms. Am. J. Sociol. 110: 1009 – 1040.en_US
dc.identifier.citedreferenceCentola, D. 2010. The spread of behavior in an online social network experiment. Science 329: 1194.en_US
dc.identifier.citedreferenceFlache, A. & M.W. Macy. 2011. Small worlds and cultural polarization. J. Math. Sociol. 35: 146 – 176.en_US
dc.identifier.citedreferenceMcPherson, M., L. Smith‐Lovin & J.M. Cook. 2001. Birds of a feather: homophily in social networks. Ann. Rev. Sociol. 27: 415 – 444.en_US
dc.identifier.citedreferenceHall, K.D. 2010. Predicting metabolic adaptation, body weight change, and energy intake in humans. Am. J. Physiol. Endocrinol. Metab. 298: E449 – E466.en_US
dc.identifier.citedreferenceMifflin, M.D. et al. 1990. A new predictive equation for resting energy expenditure in healthy individuals. Am. J. Clin. Nutr. 51: 241 – 247.en_US
dc.identifier.citedreferenceButcher, J.C. 2003. Numerical Methods for Ordinary Differential Equations. New York: John Wiley & Sons.en_US
dc.identifier.citedreferenceStriegel‐Moore, R.H. et al. 1996. Weight‐related attitudes and behaviors of women who diet to lose weight: a comparison of black dieters and white dieters. Obes. Res. 4: 109 – 116.en_US
dc.identifier.citedreferenceFrench, S.A., R.W. Jeffrey & D. Murray. 1999. Is dieting good for you? Prevalence, duration and associated weight and behaviour changes for specific weight loss strategies over four years in US adults. Int. J. Obes. Relat. Metab. Disord. 23: 320 – 327.en_US
dc.identifier.citedreferenceKnäuper, B. et al. 2005. Self‐set dieting rules: adherence and prediction of weight loss success. Appetite 44: 283 – 288.en_US
dc.identifier.citedreferenceDansinger, M.L., J.A. Gleason & J.L. Griffith. 2005. Comparison of the Atkins, Ornish, Weight Watchers, and Zone Diets for weight loss and heart disease risk reduction: a randomized trial. J. Am. Med. Assoc. 293: 43 – 53.en_US
dc.identifier.citedreferenceBureau of Labor Statistics. 2012. U.S. Department of Labor. National Longitudinal Survey of Youth 1997 cohort, 2006–2010 (rounds 10–14) [computer file]. Columbus, OH: Produced by the National Opinion Research Center, the University of Chicago and distributed by the Center for Human Resource Research, The Ohio State University.en_US
dc.identifier.citedreferenceFlegal, K.M., M.D. Carroll, B.K. Kit & C.L. Ogden. 2012. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999–2010. JAMA 307: 491 – 497.en_US
dc.identifier.citedreferenceOgden, C.L., M.D. Carroll, B.K. Kit & K.M. Flegal. 2012. Prevalence of obesity and trends in Body Mass Index among US children and adolescents, 1999–2010. JAMA 307: 483 – 490.en_US
dc.identifier.citedreferenceSwinburn, B.A. et al. 2011. The global obesity pandemic: shaped by global drivers and local environments. Lancet 378: 804 – 814.en_US
dc.identifier.citedreferenceThompson, D. et al. 2001. Body mass index and future healthcare costs: a retrospective cohort study. Obes. Res. 9: 210 – 218.en_US
dc.identifier.citedreferenceFinkelstein, E.A. et al. 2009. Annual medical spending attributable to obesity: payer‐ and service‐specific estimates. Health Aff. (Millwood) 28: w822 – w831.en_US
dc.identifier.citedreferenceHammond, R.A. & R. Levine. 2010. The economic impact of obesity in the United States. Diabetes Metab. Syndr. Obes. 3: 285 – 295.en_US
dc.identifier.citedreferenceHuang, T.T.‐K. & T.A. Glass. 2008. Transforming research strategies for understanding and preventing obesity. JAMA 300: 1811 – 1813.en_US
dc.identifier.citedreferenceHammond, R.A. 2009. Complex systems modeling for obesity research. Prev. Chron. Dis. 6: A97.en_US
dc.identifier.citedreferenceBurke, M. & F. Heiland. 2006. Social dynamics and obesity. Public Policy Discussion Papers: Federal Reserve Bank of Boston 2006; No. 06‐5.en_US
dc.identifier.citedreferenceChristakis, N.A. & J.H. Fowler. 2007. The spread of obesity in a large social network over 32 years. N Engl. J. Med. 357: 370 – 379.en_US
dc.identifier.citedreferenceValente, T.W. et al. 2009. Adolescent affiliations and adiposity: a social network analysis of friendships and obesity. J. Adolesc. Health 45: 202 – 204.en_US
dc.identifier.citedreferenceKoehly, L.M. & A. Loscalzo. 2009. Adolescent obesity and social networks. Prev. Chron. Dis. 6: A99.en_US
dc.identifier.citedreferenceCosta‐Font, J., D. Fabbri & J. Gil. 2010. Decomposing cross‐country differences in levels of obesity and overweight: does the social environment matter? Social Sci. Med. 70: 1185 – 1193.en_US
dc.identifier.citedreferenceLeahey, T.M. et al. 2011. Social influences are associated with BMI and weight loss intentions in young adults. Obesity 19: 1157 – 1162.en_US
dc.identifier.citedreferenceHammond, R.A. 2010. Social influence and obesity. Curr. Opin. Endocrinol. Diabetes Obes. 17: 467 – 471.en_US
dc.identifier.citedreferenceBahr, D.B. et al. 2009. Exploiting social networks to mitigate the obesity epidemic. Obesity 17: 723 – 728.en_US
dc.identifier.citedreferenceShoham, D.A. et al. 2012. An actor‐based model of social network influence on adolescent body size, screen time, and playing sports. PLoS ONE 7: e39795.en_US
dc.identifier.citedreferenceHammond, R.A. & J.M. Epstein. 2007. Exploring price‐independent mechanisms in the obesity epidemic. Center on Social and Economic Dynamics Working Paper No. 48.en_US
dc.identifier.citedreferenceCialdini, R.B. & M.R. Trost. 1998. Social influence: social norms, conformity, and compliance. In The Handbook of Social Psychology. G. Lindzey, D. Gilbert, S.T. Fiske, Eds.: 151 – 192. Oxford: Oxford University Press.en_US
dc.identifier.citedreferenceBrown, H. et al. 2009. Observable weight distributions and children's individual weight assessment. Obesity (Silver Spring) 18: 202 – 205.en_US
dc.identifier.citedreferenceMueller, A. et al. 2010. Sizing up peers: adolescent girls’ weight control and social comparison in the school context. J. Health Soc. Behav. 51: 64 – 78.en_US
dc.identifier.citedreferenceBurke, M.A., F.W. Heiland & C.M. Nadler. 2010. From “overweight” to “about right”: evidence of a generational shift in body weight norms. Obesity 18: 1226 – 1234.en_US
dc.identifier.citedreferenceAxelrod, R. 2006. Agent‐based modeling as a bridge between disciplines. Handbook Comput. Econ. 2: 1565 – 1584.en_US
dc.identifier.citedreferenceEpstein, J.M. 2007. Generative Social Science. Princeton, NJ: Princeton University Press.en_US
dc.identifier.citedreferenceAuchincloss, A.H. & A.V. Diez Roux. 2008. A new tool for epidemiology: the usefulness of dynamic‐agent models in understanding place effects on health. Am. J. Epidemiol. 16: 1 – 8.en_US
dc.identifier.citedreferenceMaximova, K. et al. 2008. Do you see what I see? Weight status misperception and exposure to obesity among children and adolescents. Int. J. Obes. 32: 1008 – 1015.en_US
dc.identifier.citedreferenceAriely, D. 2001. Seeing sets: representation of statistical properties. Psychol. Sci. 12: 157 – 162.en_US
dc.identifier.citedreferenceCavanagh, P. 2001. Seeing the forest but not the trees. Nat. Neurosci. 4: 673 – 674.en_US
dc.identifier.citedreferenceChong, S.C. & A. Treisman. 2003. Representation of statistical properties. Vision Res. 43: 393 – 404.en_US
dc.identifier.citedreferenceChong, S.C. & A. Treisman. 2005. Statistical processing: computing the average size in perceptual groups. Vision Res. 45: 891 – 900.en_US
dc.identifier.citedreferenceAlvarez, G.A. 2011. Representing multiple objects as an ensemble enhances visual cognition. Trends Cogn. Sci. 15: 122 – 131.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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